• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2004년도 추계학술대회
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• pp.234-239
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• 2004

This paper describes preliminary results we have obtained in developing a computer vision system based on active IR illumination for real time gaze tracking for interactive graphic display. Unlike most of the existing gaze tracking techniques, which often require assuming a static head to work well and require a cumbersome calibration process fur each person, our gaze tracker can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using the Generalized Regression Neural Networks (GRNN). With GRNN, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. The effectiveness of our gaze tracker is demonstrated by preliminary experiments that involve gaze-contingent interactive graphic display.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.32-39
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• 2023

This paper provides a comprehensive overview of UAV classification, tracking, and detection, offering researchers a clear understanding of these fundamental concepts. It elucidates how classification categorizes UAVs based on attributes, how tracking monitors real-time positions, and how detection identifies UAV presence. The interconnectedness of these aspects is highlighted, with detection enhancing tracking and classification aiding in anomaly identification. Moreover, the paper emphasizes the relevance of simulations in the context of drones and UAVs, underscoring their pivotal role in training, testing, and research. By succinctly presenting these core concepts and their practical implications, the paper equips researchers with a solid foundation to comprehend and explore the complexities of UAV operations and the role of simulations in advancing this dynamic field.

• 융합신호처리학회논문지
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• 제23권2호
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• pp.70-75
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• 2022

각종 디지털 기기의 보급으로 현대사회는 기기들이 일상화되었다. 더욱이 COVID-19라는 팬데믹 동안 실내에 머무르면서 기기 사용량의 증가와 온라인 학습의 증가로 눈 피로도에 따른 어린이들의 근시 증가, 젊은 노안 증가, 안구 건조증과 같은 증상이 증가하고 있고, 이제는 눈 건강에 대한 관심이 예전과 다르다. 눈 건강에 대한 처방은 여러 가지가 있지만 본 논문에서는 VR 콘텐츠를 활용한 시기능 강화 훈련 방법을 제안하고자 한다. 시기능 강화 훈련에 관한 기존의 교구에 의한 아날로그 방법들을 디지털 콘텐츠로 기획 및 제작하였으며, 일반 시기능 훈련센터에서 교구를 가지고 진행하는 다양한 방법 중 콘텐츠화가 가능한 7가지의 방법을 선택하여 VR 기반의 훈련콘텐츠로 개발하였다. 각 콘텐츠의 훈련 과정에서 사용자에게 훈련의 참여에 대한 피드백을 주기 위해 VR 기기에 아이트래킹을 적용하여 훈련 과정에 대한 관리와 집중도를 분석할 수 있도록 제안하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4929-4947
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• 2017

In visual object tracking, Correlation Filter-based Tracking (CFT) systems have arouse recently to be the most accurate and efficient methods. The CFT's circularly shifts the larger search window to find most likely position of the target. The need of larger search window to cover both background and object make an algorithm sensitive to the background and the target occlusions. Further, the use of fixed-sized windows for training makes them incapable to handle scale variations during tracking. To address these problems, we propose two layer target representation in which both global and local appearances of the target is considered. Multiple local patches in the local layer provide robustness to the background changes and the target occlusion. The target representation is enhanced by employing additional reversed RGB channels to prevent the loss of black objects in background during tracking. The final target position is obtained by the adaptive weighted average of confidence maps from global and local layers. Furthermore, the target scale variation in tracking is handled by the statistical model, which is governed by adaptive constraints to ensure reliability and accuracy in scale estimation. The proposed structural enhancement is tested on VTBv1.0 benchmark for its accuracy and robustness.

• 한국멀티미디어학회논문지
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• 제24권2호
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• pp.328-335
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• 2021

In the era of 'Untact', virtual reality-based job training platforms are actively being used as part of non-face-to-face education for students with developmental disabilities. Because the people with developmental disabilities may lack sufficient cognitive abilities, it is difficult to conduct untact training seamlessly without the help of a third party. Therefore, it is necessary for training programs to identify the right timing to provide help so that the training can be continued. This research analyzed the visual attention of students with developmental disabilities in virtual reality-based job training program in order to determine the point of time when an intervention is required by the trainee. Results showed that students who completed the mission tended to have intense visual attention on a small number of objects for a certain period of time; the visual attention of the students who failed tended to shift erratically among multiple objects.

• 한국멀티미디어학회논문지
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• 제9권10호
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• pp.1266-1275
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• 2006

본 논문은 AdaBoost(Adaptive Boosting)알고리즘을 이용한 실시간 얼굴 검출 및 추적에 패한 기법을 제안한다. 얼굴 검출은 8종류의 간단한 웨이블릿 특징 모형을 이용한다. 각각의 특징들은 $20{\times}20$의 훈련 영상에서 다양한 크기와 위치로 배치되어 초기의 특징 집합을 구성한다. 초기의 특징 집합과 훈련 영상은 AdaBoost알고리즘의 입력으로 사용된다. AdaBoost알고리즘의 기본원리는 약한 분류기를 선형적으로 결합하여 최종적으로는 계층적 구조를 갖는 강한 분류기론 생성하는 것이다. 본 논문에서는 AdaBoost알고리즘에서 훈련 영상과 초기의 특징 집합 간에 이루어지는 반복적 계산량을 줄이기 위해 SAT(Summed-Area Table) 기법을 이용하였다. 얼굴 추적은 Pan-Tilt카메라를 통해 동적으로 가시 영역을 확장해 가면서 검출된 영역의 위치와 크기정보를 이용하여 실시간으로 이루어진다. 검출된 얼굴 영역의 중심을 전체 영상의 중심으로 이동하는 방법을 사용하였다. 실험결과 92.5%의 얼굴 검출율과 평균 12프레임의 얼굴 추적속도를 얻었다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.126-130
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• 2001

In this paper, we propose the design methodology of target tracking system using fuzzy basis function expansion (FBFE) based on virus evolutionary genetic algorithm(VEGA). In general, the objective of target tracking is to estimate the future trajectory of the target based on the past position of the target obtained from the sensor. In the conventional and mathematical nonlinear filtering method such as extended Kalman filter (EKF), the performance of the system may be deteriorated in highly nonlinear situation. To resolve these problems of nonlinear filtering technique, by appling artificial intelligent technique to the tracking control of moving targets, we combine the advantages of both traditional and intelligent control technique. In the proposed method, after composing training datum from the parameters of extended Kalman filter, by combining FBFE, which has the strong ability for the approximation, with VEGA, which prevent GA from converging prematurely in the case of lack of genetic diversity of population, and by identifying the parameters and rule numbers of fuzzy basis function simultaneously, we can reduce the tracking error of EKF. Finally, the proposed method is applied to three dimensional tracking problem, and the simulation results shows that the tracking performance is improved by the proposed method.

• 지능정보연구
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• 제25권4호
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• pp.53-65
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• 2019

영상 기반의 보안 시스템의 증가함에 따라 각 용도마다 다른 다양한 객체들에 대한 처리들이 중요해지고 있다. 객체 추적은 객체 인식, 검출과 같은 작업들과 함께 필수적인 작업으로 다뤄진다. 이 객체 추적을 달성하기 위해서 다양한 머신러닝이 적용될 수 있다. 성공적인 분류기로써 전체 에러율 최소화(total-error-rate minimization) 기반의 방법론이 사용될 수 있다. 이 전체 에러율 최소화 기반의 방법론은 오프라인 학습을 기반으로 하고 있다. 객체 추적은 실시간으로 처리하며 갱신해야하는 것이 필수적이므로 온라인 학습(online learning)을 기반으로 하는 것이 적합하다. 온라인 전체 에러율 최소화 방법론이 개발되었지만 점근적으로 재가중되는(approximately reweighted) 작업이 포함되어 에러를 누적시킬 수 있다는 단점이 있다. 본 논문에서는 정확하게 재가중되는(exactly reweighted) 방법론을 제안하면서 온라인 전체 에러율 최소화가 달성되었다. 이 제안된 온라인 학습 방법론을 객체 추적에 적용하여 총 8개의 데이터베이스에서 다른 추적 방법론들 보다 좋은 성능이 달성되었다.

• 대한인간공학회지
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• 제19권2호
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• pp.47-61
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• 2000

To study the characteristic of the weight center control of humans, the tracking control capability of circular and wave motion by weight center movement was conducted by using the force platform. The control performance(the integrated value of the $|Object\;value(X)-Control\;Value(Y)|^{2}$) and control trace record was used to evaluate the individual performance characteristics. The size of the population for this study was 73, which consisted of engineering students, students majoring in taekwondo, students majoring in dance, all of which were in their twenties, and also people in their sixties. The results of this study indicate that the weight center control characteristics of humans can be represented by the evaluation method and values. People who were capable of tracking the object did not stop nor overshot the objective. In addition, habits or training characteristics and aging seemed to influence the performance of the subjects. In the future, development of different objectives for weight center control could be used to determine the severity of the disease of the subject and the effects of the treatment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권1호
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• pp.17-25
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• 2014

This paper presents the formulation of an impedance controller for regulating the contact force with the environment. To achieve an accurate force tracking control, uncertainties in both robot dynamics and the environment require to be addressed. As part of the framework of the proposed force tracking formulation, a neural network is introduced at the desired trajectory to compensate for all uncertainties in an on-line manner. Compensation at the input trajectory leads to a remarkable structural advantage in that no modifications of the internal force controllers are required. Minimizing the objective function of the training signal for a neural network satisfies the desired force tracking performance. A neural network actually compensates for uncertainties at the input trajectory level in an on-line fashion. Simulation results confirm the position and force tracking abilities of a robot manipulator.